Virtualisation Cloud Computing at the RAL Tier 1. Ian Collier STFC RAL Tier 1 HEPiX, Bologna, 18 th April 2013

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1 Virtualisation Cloud Computing at the RAL Tier 1 Ian Collier STFC RAL Tier 1 HEPiX, Bologna, 18 th April 2013

2 RAL Context at RAL Hyper-V Services Platform Scientific Computing Department Cloud GridPP Cloud Project

3 What Do We Mean By Cloud For these purposes does not require administrator intervention Service owners don t have to care about where things run

4 Context at RAL Historically requests for systems went to fabric team Procure new HW could take months Scavenge old WNs could take days/weeks Kickstarts & scripts took tailoring for each system Not very dynamic For development systems many users simply run VMs on their desktops hard to track & risky

5 Evolution at RAL Many elements play their part Configuration management system Quattor (introduced in 2009) abstracts hardware from os from payload, automates most deployment Makes migration & upgrades much easier (still not completely trivial) Databases feeding and driving configuration management system Provisioning new hardware much faster

6 Virtualisation & RAL Context at RAL Hyper-V Services Platform Scientific Computing Department Cloud WLCG Related Cloud

7 Hyper-V Platform Over last three years Local storage only in production ~200 VMs Provisioning transformed Much more responsive to changing requirements Self service basis requires training all admins in using management tools but this Progress of high availability shared storage platform (much) slower than we d have liked Planning move to production now

8 Hyper-V Platform

9 Hyper-V Platform Mostgrid services virtualised now argus, apel, bdii, cream-ce, fts, myproxy, ui, wms, etc. Internal databases & monitoring systems Also test beds (batch system, CEs, bdiis etc) Move to production very smooth Team had good period to become familiar with environment & tools

10 Hyper-V Platform When a Tier 1 admin needs to set up a new machine all they have to request is a DNS entry Everything else they do themselves Maintenance of underlying hardware platform can be done with (almost) no service interruption. This is already much, much better especially more responsive than what went before. Has many characteristics of private cloud But we wouldn t usually call it cloud

11 Hyper-V Platform However, Windows administration is not friction or effort free (we are mostly Linux admins.) Share management server with STFC corporate IT but they do not have resources to support our use Troubleshooting means even more learning Some just don t like it Hyper-V continues to throw up problems supporting Linux None show stoppers, but they drain effort and limit things Ease of management otherwise compensates for now Much better with latest SL (5.9 & 6.4) Since we began open source tools have moved on We are not wedded to Hyper-V

12 Virtualisation & RAL Context at RAL Hyper-V Services Platform Scientific Computing Department Cloud WLCG Related Cloud

13 SCD Cloud Prototype E-Science Department cloud platform Began as small experiment 18 months ago Using StratusLab Share Quattor configuration templates with other sites Very quick and easy to get working But has been a moving target as it develops Deployment done by graduates on 6 month rotation Disruptive & variable progress

14 SCD Cloud Initially treat systems much like any Tier 1 system We allow users in whom we have high levels of trust Monitor that central logging is active, sw updates are happening Cautiously introducing new user groups Plan to implement further network separation Waiting for reorganisation of Tier 1 Network Martin spoke about

15 SCD Cloud Resources Began with 20 (very) old worker nodes Current ~80 cores Filled up very quickly 1 year ago added 120 cores in new Dell R410s and also a few more old WNs This month adding 160 cores in more R410s ~300 cores enough to continue development to cover further use cases Run a meaningful test bed

16 SCD Cloud Usage 30 or so regular users (dept of ~200) ~100 VMs at any one time Typically running at 90-95% full Exploratory users from other departments Also adding very selective external (GridPP) users Proof of concept more than successful Full time permanent staff in plan It is busy lots of testing & development People notice when it is not available

17 SCD Cloud Future Develop to full resilient service to users across STFC Participation in cloud federations Have been evaluating storage solutions For image store/sharing and S3 storage service Ceph looks very promising for both Have new hardware delivered for 80TB ceph cluster Will be deploying in coming weeks Integrating cloud resources in to Tier 1 grid work Reexamine platform itself. Things have moved on since we started with StratusLab

18 Virtualisation & RAL Context at RAL Hyper-V Services Platform Scientific Computing Department Cloud WLCG Related Cloud

19 WLCG Related Cloud Dynamically-provisioned worker nodes Allow a traditional batch system to make opportunistic use of cloud resources by dynamically creating worker nodes Testing two implementations: HTCondor A service monitors the state of the pool which creates & destroys VMs as necessary. Condor startd daemons on each VM then advertise themselves to the Condor collector. SLURM Makes use of existing power save logic: instead of powering up & down nodes, the SLURM controller creates & destroys VMs as necessary.

20 WLCG Related Cloud CMS UK cloud activities Enabling CMS analysis jobs to be run on cloud resources in the UK Users run the standard CMS tool (CMS Remote Analysis Builder) to create & submit jobs GlideinWMS system at RAL instantiates VMs as needed & creates an on-demand overlay HTCondor batch system for running the user jobs

21 Virtualisation & RAL Context at RAL Hyper-V Services Platform Scientific Computing Department Cloud WLCG Related Cloud

22 Summary Using range of technologies Many ways our provisioning & workflows have become more responsive, agile Private cloud has developed from a small experiment to beginning to provide real services With constrained effort Slower than we would have liked The experimental platform is proving well used We look forward to being able to replace Hyper-V for resilient services

23 Backup Slides

24 JASMIN/CEMS The JASMIN super-data-cluster UK and European climate and earth system modelling community. Climate and Environmental Monitoring from Space (CEMS) Facilitating further comparison and evaluation of models with data. 6.6 PB Storage Panasas at STFC Fast Parallel IO to Compute servers (370 Cores) Gnodal 10GB networking

25 JASMIN/CEMS

26 JASMIN Super Data Cluster JASMIN CEMS 3.5 PetaBytes Panasas Storage 20 x Dell R610 (12 core, 3.0GHz, 96G RAM) 1 x Dell R815 (48 core, 2.2GHz, 128G RAM) 1 x Dell Equallogic R6510E (48 TB iscsi VM image store) VMWare vsphere Center 1 x Force10 S4810P 10GbE Storage Aggregation Switch 1.1 PetaBytes Panasas Storage 7 x Dell R610 (12 core 96G RAM)Servers 1 x Dell Equallogic R6510E (48 TB iscsi VMware VM image store) VMWare vsphere Center + vcloud Director

27 JASMIN Super Data Cluster JASMIN provides three classes of service: Virtualised compute environment (not strictly a "private cloud ). Physical compute environment. No private data connection HPC service ("Lotus"). Not easily reconfigurable to JASMIN cloud. Separate data connection.

28 JASMIN Super Data Cluster Two distinct clouds One supports manual VM provisioning by CEDA and the climate HPC community Configuration controlled at site Therefore greater trst and greater network access One supports more dynamic provisioning by the academic users in the CEMS community. Users provision own VMs Access to Panasas Otherwise less trusted So, they have different vcentre server installations.

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